Camera Models

COLMAP implements different camera models of varying complexity. If no intrinsic parameters are known a priori, it is generally best to use the simplest camera model that is complex enough to model the distortion effects:

  • SIMPLE_PINHOLE, PINHOLE: Use these camera models, if your images are undistorted a priori. These use one and two focal length parameters, respectively. Note that even in the case of undistorted images, COLMAP could try to improve the intrinsics with a more complex camera model.

  • SIMPLE_RADIAL, RADIAL: This should be the camera model of choice, if the intrinsics are unknown and every image has a different camera calibration, e.g., in the case of Internet photos. Both models are simplified versions of the OPENCV model only modeling radial distortion effects with one and two parameters, respectively.

  • OPENCV, FULL_OPENCV: Use these camera models, if you know the calibration parameters a priori. You can also try to let COLMAP estimate the parameters, if you share the intrinsics for multiple images. Note that the automatic estimation of parameters will most likely fail, if every image has a separate set of intrinsic parameters.

  • SIMPLE_RADIAL_FISHEYE, RADIAL_FISHEYE, OPENCV_FISHEYE, FOV, THIN_PRISM_FISHEYE, RAD_TAN_THIN_PRISM_FISHEYE: Use these camera models for fisheye lenses and note that all other models are not really capable of modeling the distortion effects of fisheye lenses. The FOV model is used by Google Project Tango (make sure to not initialize omega to zero).

You can inspect the estimated intrinsic parameters by double-clicking specific images in the model viewer or by exporting the model and opening the cameras.txt file.

To achieve optimal reconstruction results, you might have to try different camera models for your problem. Generally, when the reconstruction fails and the estimated focal length values / distortion coefficients are grossly wrong, it is a sign of using a too complex camera model. Contrary, if COLMAP uses many iterative local and global bundle adjustments, it is a sign of using a too simple camera model that is not able to fully model the distortion effects.

You can also share intrinsics between multiple images to obtain more reliable results (see Share intrinsic camera parameters) or you can fix the intrinsic parameters during the reconstruction (see Fix intrinsic camera parameters).

Please, refer to the camera models header file for information on the parameters of the different camera models: https://github.com/colmap/colmap/blob/main/src/colmap/sensor/models.h